Empfohlen
Empfohlen
Weitere ähnliche Inhalte
Was ist angesagt?
Was ist angesagt? (11)
Ähnlich wie Searching for pharmacokinetic data in Pharmapendium
Ähnlich wie Searching for pharmacokinetic data in Pharmapendium (20)
Mehr von Ann-Marie Roche
Mehr von Ann-Marie Roche (20)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
Searching for pharmacokinetic data in Pharmapendium
- 1. Welcome to our PharmaPendium Webinar! Pharmacokinetics module Your host: Ann-Marie Your presenter: Pooja Jain Roche 1/9
- 2. About us 2/9
- 3. Need to know Webinar control panel: ‘chat’ or ‘ask a question’ for questions and comments Option for full screen view Q&A after presentation 3/9
- 4. Pharmacokinetics Module: Value Unprecedented access to Preclinical and Clinical exposure data extracted from FDA packages (current & historic) and EMEA documents. • ~2,000 drugs with preclinical and clinical exposure data at multiple parameters and usually under various experimental conditions: • Concomitant drugs, disease states, demographic differences, etc. • The level of PK data to be contained in this database is almost never published (competitive reasons) at this level of detail. Pharmacokinetics, preclinical and clinical, & Drug Safety databases browsable within the same platform. 4/9
- 5. Pharmacokinetics Module: Content Extracted parameter values for at least 2,000 drugs, taken from : • FDA Reviews from 1938-Present (FDA Approval Packages) • If you do not have FDA Classic Collection, you will have acesss to extracted data, and citation, but will not be able to drill-in to the original document. • EMEA EPARs from ~1995 – Present 5/9
- 6. Pharmacokinetics Module: Content • Will contain an estimated 1.25 million lines of extracted pharmacokinetics observations • With filterable fields and special designations for: • Drug name, Species, Study Group (population), Dose, Route, Parameter, Value (normalized in searching), SD • Enantiomers, Metabolites, Tissue-specific studies, Concomitants (Food Effects) 6/9
- 7. Pharmacokinetics Module: Sample Uses Creating Modeling Sets: valuable data in modeling therapeutic window for new drugs Drug Development Project assessments • A newly-available wealth of comparative data to aid in development candidates’ decisions, prioritizations, and direction. 7/9
- 8. Pharmacokinetics Module: Sample Uses Competitive Opportunity: • Can we deliver this drug better than our competitors? • Where has the bar been set in this drug class? • Where are the opportunities in Drug Class X using our proprietary methods / formulations? 8/9
- 9. Let’s go to www.pharmapendium.com 9/9
- 10. How may I find protein binding data for the same drug in animal and human studies? Check notes for all solutions in PP 10/X
- 11. Now let’s see what kind of data we can find if we look up for example, a drug called Aromasin, a prescription medicine for the treatment of breast cancer. Check notes for all solutions in PP 11/X
- 12. Now let’s look for protein binding differences for another drug, Rosuvastatin. Rosuvastatin is a member of the drug class statins and is used for lowering cholesterol. Now if we go under clinical data and select for bioavailability, I would like to show you what other types of insights you can get. Check notes for all solutions in PP 12/X
- 13. POLL The poll should appear on your screen shortly…. 13/9 13
- 14. So if we want to see how we can find metabolite data using the PK module in PP, let’s click on the PK tab. Check notes for all solutions in PP 14/X
- 15. Now, if we want to see how we can find Cmax data using the PK module in PP, based on what you have seen already, we can probably not only look for Cmax data, but also ask questions like, is Cmax affected by fed vs fasted states? Will this in turn affect the bioavailability of the drug? Check notes for all solutions in PP 15/X
- 16. So now, if we want to find some interesting Tmax data, which is data pertaining to how long it takes to reach Cmax, we can for example look at analgesics. So we can go under drugs and drug classes. Click on analgesics and add it. Then under the PK parameters, we can click on Distribution, then time values, and then tmax. Then we click search now. And here you can see all the results. Check notes for all solutions in PP 16/X
- 17. Questions & Answers 17/9
- 18. The Q&A will be sent to you by email. For more information and questions please contact bdtraining@elsevier.com The next PharmaPendium webinar is an introductory webinar and will be on the 27th of June. Go to www.trainingdesk.elsevier.com/pharmapendium for all training related materials. Please fill out the survey that appears on your screen after leaving the webinar. 18/9
Hinweis der Redaktion
- Welcome to this webinar about PharmaPendium, focusing on finding Pharmacokinetic data. My name is Ann-Marie and I am your host today. I am here with our PharmaPendium expert Pooja Jain. Pooja comes with over 10 years of experience in the life sciences industry where she has experience working, for example, at Mimetogen Pharmaceuticals and Eli Lilly. Pooja has both a Master’s in Molecular Biology and an MBA degree and is here to educate us more on the pharmacokinetic module of PharmaPendium, such as how you may make drug development project risk assessments, identify competitive opportunities in a therapeutic area or drug class and gain critical understanding to potential pharmacokinetic responses by looking at critical data such as food effects, concomitant drugs, co-morbidities and demographic effects. We will be placing this webinar online so you can listen to it again, at your own pace! This webinar is aimed at users with some experience with PP. Introductions to PP are also offered and the next introductory webinar is scheduled for June 27 th .
- Before we get started, I would briefly like to put PharmaPendium into context with the other activities that go on at Elsevier. Elsevier serves 3 main and interlinked areas, some of which may be of interest to you, Biology, Chemistry and Medicine. [first click] Pharmapendium, gives you searchable access to all FDA and EMA approval documentation and we also provide additional solutions serving the biology and medicine spheres, such as Embase for your biomedical literature searching needs, SciVerse ScienceDirect for full-text access and SciVerse Scopus, an all-science abstract and citation database. [second click] This should help put PharmaPendium into context, and with that we are almost ready to move to today’s session, which Pooja will be taking us through.
- Just before we get started, a couple of need to knows. During the session you may send us your questions by using the chat or Ask a Question function on the webinar control panel. We will have 15 minutes for questions at the end and for those questions we do not answer in the webinar, they will be included in a complete Q&A sent to all attendees by email. If you wish to have a full screen view, please click on the red arrow. Your control panel will be hidden. Click again on the red arrow to see your control panel again. Pooja, welcome, could you briefly introduce yourself and tell us all about PharmaPendium?
- Well let’s take the drug Enablex. Enablex is a prescription medicine used in adults for the treatment of overactive bladder. Let’s see what kind of information we can find regarding protein binding in animal and human studies. We can search for Enablex under the add drugs and drug classes tab by searching under the “A-Z” tab. We go under “E” and we can find “enablex” here. We add this and we can rightaway select for protein binding data. Let’s narrow the search down to plasma protein binding and then click search. Now we can see that the results can be sorted by species. We can see that there is data present for studies done in dogs, humans, rabbits and rats. We can see that there is a lot of plasma protein data present. By looking at this data, we can see that we can gain some interesting insight. For one, if we look at results 5 & 6, we can see that by increasing the dose by 5x, the plasma protein binding does not significantly change in dogs. However, if we look at lines 10 & 11, we can see that by increasing the dose by up to 5x, the plasma protein binding changes by greater than 90%! This can in part explain why adverse events were seen at higher doses. And this is an example of how PP can significantly influence the way in which you design your preclinical studies.
- Besides finding a drug using the method I showed before, we can also go under the general search tab and type the drug of interest. So if we type Aromasin in the search bar, we can then directly click on the pharmacokinetics data link. Now here, because we are looking for all pharmacokinetic data, we will see the preclinical and clinical view. Under the preclinical tab, let’s filter and look at bioavailability data. If we click on show filters tab and click “absorption” and then click on bioavailability, we can see how in dogs and rats, the bioavailability is hovering under 5%. If we now do the same thing on the clinical data tab, we can see that the data is drastically different and the parameter value is actually 86%. This is an example of how having the PK module in PP can really help you mitigate risk when planning your preclinical studies. If you click on the second result, you can see from where they got the data, and in addition, you can find additional interesting information from there.
- Here you can see that if we look at the study group and scroll down, we can actually see ethnic differences for bioavailability with Japanese groups having a higher bioavailability than caucasions. Could be a very interesting thing to know if you are looking to penetrate different markets with your drug. This kind of comparative data can really make a big difference!
- We go under drugs and drug classes, and we can as an example click on cholinesterase inhibitors. We click add. We can then expand the PK parameters and go under biotransformation and see what %age of the drug dose in transformed into metabolites. Click on metabolic transformation and then “search now” and then we can see all of the relevant data. Look at donepezil hydrochloride and see how you can get extra information when you click on the link in regards to studies done on dogs. Now if we go back, we can see what the data is like in humans. If available, we can even see the metabolite of interest in the parentheses. If we scroll a little bit and look at the data provided in this table, we can actually see that the metabolite “o-glucuronides” is present in both dogs and rats, but possibly not in humans suggesting perhaps a species specific metabolite which would be interesting to know upfront without having to spend too much time wondering if this is something that you need to maybe worry about in humans.
- As an example, let’s look at the drug Acebutolol Hydrochloride or Acebutolol. Again we click on the PK tab and now we can for example go under clinical data and find some interesting data in humans. We can filter by clicking on absorption, and then on concentration, and then we can actually select for Cmax. As a side note, we can actually see that this data is from 1984, and this data would actually be present in the classic collection of PP which has data from 1938 till 1991 inclusive. This could be interesting info if, for example, you are looking at PK data for repositioning this drug on the market. So from looking at this data, we can actually see that by doubling the dose, we can also almost double the Cmax value. Now if we click, on let’s say the 3 rd result because it actually also shows us data on the metabolite, we can actually see that it gives us further interesting information. It actually says that “the study demonstrated that although non-fasting conditions resulted in a decrease in the rate and the peak levels of acebutolol absorbed and metabolized by these healthy volunteers, there was no significant difference in the actual bioavailability. And here is a table which shows further info. Obviously some very interesting comparative data here for drug development studies.
- As I scroll down you can see all of the interesting data that is available. Now it is pretty straightforward to see all of the data that is available. But let’s see if we can find an example of some interesting data we can find with combinatorial drugs. If we scroll down, we can see data on a combinatorial administration of acetaminophen, asprin and caffeine. Here you can see that you have the doses of all three substances listed here. Now if we click on the link to go straight to the document, we can see the wealth of data that is present in the document itself. It actually presents data in comparison to different forms of the drug, tablet, caplets and geltaps. And you can actually see at the end after scrolling through all this data that the concentrations of the combinatorial drugs is not affected by extra strength acetaminophen which is Excedrin. This data can be really useful if for example you are doing similar combinatorial drug studies. This data can potentially be cited and could maybe help you avoid repeating studies which can save you a lot of time and money. Now let’s see if we have time to go through one more example. Let’s quickly go back and scroll down a bit further till we get to this result where again we see combinatorial drug administration. However here, under Tmax, we actually see them mention a metabolite. If we click on the link and scroll down to the Pharmacokinetic section, we can actually see that there is a difference in PK profiles of tramadol but not acetaminophen when administered together. (see second line of paragraph under the table and the last line). Acetaminophen affects the PK profile of tramadol and the metabolites, but not vice versa. Could be some very interesting data to keep in mind when doing drug development studies. And also something to keep in mind is that this data where we see one drug being affected by acetaminophen is different from the previous example I showed where acetaminophen did not significantly affect the PK profiles of the other combinatorial drugs. Hence being fully informed on the comparative data which can be available to you is critical in order to properly plan out your preclinical and clinical studies.